This proposal is focused on the identification of predictors of disease progression in hepatitis C (HCV) infection. We will examine the influence of the immune response on the natural history in two cohorts; immune compromised liver transplant patients and immune competent patients with HCV. Our primary hypothesis is that fibrosis progression is accelerated by immune suppression. Our secondary hypothesis is that type of immune suppression and ethnicity contribute to fibrosis progression. We will use databases of patients who have undergone liver transplantation and immune competent patients who have undergone liver biopsy, databases which include clinical, demographic, biochemical and histological data as well as information regarding risk exposures and alcohol consumption. All liver biopsies have been graded and staged for the degree of inflammation and fibrosis respectively. Serum is available from the majority. Initial analysis of 284 liver transplant recipients showed that post-transplantation fibrosis progression was linear but variable, and was independently associated with year of transplantation, non-Caucasian ethnicity, number of steroid boluses and HCV RNA level at transplantation. Since the explanation of these associations was not apparent, we expanded the transplantation databases in order to identify precisely predictors of disease progression. We will also measure variables including ethnicity in fibrosis progression in immune competent patients. In most studies of natural history, the duration of HCV infection is estimated retrospectively from time of presumed first risk exposure. Through modeling timing of exposures, we will develop an approach to assign accurately time of initial infection. We will also investigate the association between genetic diversity in the envelope and NS3 genes and disease progression. Finally, we will collect lymphocytes from HCV- infected patients for future analysis of the association between genetic markers and disease progression. These cohorts will provide lymphocytes to Dr. Greenberg to measure HCV-specific CTL response and HCV variants to Dr. Kay to measure pathogenicity of HCV in an animal model. Elucidation of the mechanisms by which HCV causes disease is essential for the identification of those at risk for serious consequences.